A radar device is known as a device that measures the position of an object existing at a remote point.
A radar device emits a wave, such as an electromagnetic wave or an acoustic wave, toward space, for example, and receives a wave which is reflected by an object which is a measurement object and returns thereto, and analyzes a received signal of the wave to measure the distance and the angle from the radar device to the object.
A weather radar device that sets fine liquid droplets or solid particles (referred to as an “aerosol” from here on) floating in atmospheric air as measurement objects, and that calculates the speed (wind speed) at which the aerosol is moving from the amount of phase rotation of a wave which is reflected by the aerosol and returns thereto is known especially among radar devices.
Further, a laser radar device that uses laser light as an electromagnetic wave, especially among weather radar devices, can observe an object with a high angular resolution and is therefore used as a wind direction and wind speed radar device because the divergence of the beam emitted thereby is very small (refer to nonpatent reference 1).
A conventional laser radar device emits laser light into atmospheric air, and, after that, receives laser light which is reflected by an aerosol existing in the atmospheric air, and returns thereto (laser light which receives a Doppler frequency shift according to the movement speed of the aerosol as the aerosol moves), and performs heterodyne detection on the laser light and local light, thereby detecting a Doppler signal corresponding to the movement speed of the aerosol (wind speed).
FIG. 14 is an explanatory drawing showing the concept of measurement by the conventional laser radar device.
The laser radar device performs a process of splitting the laser light (reflected light) reflected by the aerosol in the atmospheric air at each altitude and returns thereto into segments by time. In general, each reflected light split by time is called a “range bin.”
The laser radar device performs a coherent integration at very short intervals on each range bin, and performs a Fourier transform within the range bin.
After that, in order to improve the signal to noise ratio (referred to as SNR (Signal to Noise Ratio) from here on), the laser radar device performs N incoherent integrations on a pulse for each range bin, as shown in FIG. 15.
It is generally known that when the N incoherent integrations are performed, the SNR is improved by a factor of √N (refer to patent reference 1).
FIG. 16 is an explanatory drawing showing the concepts of a wind speed and a wind speed width which are derived from a reception spectrum.
In FIG. 16, a spectrum of wind speed which is acquired when a Gaussian beam is emitted is shown, and the peak of this spectrum is defined as a Doppler speed (wind speed).
As a method of calculating this Doppler speed, in addition to a peak detection method of calculating a Doppler speed from a frequency corresponding to a peak value of the SNR, there is a centroid calculation method of calculating the center of gravity of one or more peak values in the SNR, and calculating a Doppler speed from a frequency corresponding to the center of gravity (refer to nonpatent reference 1).
Further, there is a maximum likelihood estimation method of making variable a parameter of a waveform model of a reception spectrum prepared in advance, searching for a parameter having the highest correlation with a spectrum of a received signal, and calculating the speed of the object to be measured by using the parameter (refer to patent reference 2).
FIG. 17 is an explanatory drawing explaining a merit and a demerit of wind measurements using the peak detection method and those of wind measurements using the centroid calculation method.
When a sampling frequency is denoted by fs and the number of data points is denoted by p, a frequency resolution Δf is given by fs/p.
When a wind measurement is performed by using the peak detection method, there is a case in which no peak of the SNR can be correctly detected, as shown in FIG. 17(a), unless the sampling frequency fs is sufficient. Therefore, the wind speed acquired by using the peak detection method may have an error for its true value.
In contrast with this, when a wind measurement is performed by using the centroid calculation method, a wind measurement with accuracy greater than the frequency resolution can be implemented, as shown in FIG. 17(a).
However, when a clutter exists and noise caused by rain or the like is mixed in the received signal, as shown in FIG. 17(b), or when there occurs a statistical fluctuation, a clutter component is added to the calculation of the center of gravity, and therefore a larger error is included in the wind speed acquired by using the centroid calculation method. In such a case, the peak detection method can acquire a value closer to the true wind speed. The difference between FIG. 17(a) and FIG. 17(b) is distinguishable according to the wind speed width acquired.
The above-mentioned maximum likelihood estimation method has a merit of being able to determine a wind speed having a high degree of accuracy because it determines a parameter of a waveform model having the highest correlation with the spectrum of the received signal through repetitive calculations.
Further, there is provided an advantage of being able to reduce an SNR desirable for the wind measurement to a value smaller than that in the peak detection method (refer to nonpatent reference 2).
The maximum likelihood estimation method has another merit of, when a plurality of winds are mixing in the same range bin, being able to measure each wind speed (refer to patent reference 2). FIG. 18 is an explanatory drawing explaining a wind measurement of a plurality of winds using the maximum likelihood estimation method.
However, there is a demerit that because it is necessary to perform repetitive calculations, the speed of the calculation is slower than those in the peak detection method and the centroid calculation method, and the wind measurement rate is slow.